This invention relates to human sleepiness, drowsiness or (lack of) alertness detection and monitoring, to provide a warning indication in relation to the capacity or fitness to drive or operate (moving) machinery.
Although its rationale is not fully understood, it is generally agreed that sleep is a powerful and vital, biological need, which--if ignored--can be more incapacitating than realised, either by a sleepy individual subject, or by those tasking the subject.
As such, the invention is particularly, but not exclusively, concerned with the (automated) recognition of sleepiness and performance-impaired fatigue in drivers of motor vehicles upon the public highway.
Professional drivers of, say, long-haul freight lorries or public transport coaches are especially vulnerable to fatigue, loss of attention and driving impairment.
With this in mind, their working and active driving hours are already carefully monitored to ensure they are within prescribed limits.
Road accidents, some with no apparent external cause, have been attributed to driver fatigue.
Studies, including those by the Applicants themselves, (see the list of references at the end of this disclosure), into sleep-related vehicle accidents have concluded that such accidents are largely dependent on the time of day.
Age may also be a factor--with young adults more likely to have accidents in the early morning, whereas older adults may be more vulnerable in the early afternoon.
Drivers may not recollect having fallen asleep, but may be aware of a precursory sleepy state, as normal sleep does not occur spontaneously without warning.
The present invention addresses sleepiness monitoring, to engender awareness of a state of sleepiness, in turn to prompt safe countermeasures, such as stopping driving and having a nap.
Accidents have also been found to be most frequent on monotonous roads, such as motorways and other main roads.
Indeed, as many as 20-25% of motorway accidents seem to be as a result of drivers falling asleep at the wheel.
Although certain studies concluded that it is almost impossible to fall asleep while driving without any warning whatsoever, drivers frequently persevere with their driving when they are sleepy and should stop.
Various driver monitoring devices, such as eyelid movement detectors, have been proposed to assess fatigue, but the underlying principles are not well-founded or properly understood.
Sleepiness in the context of driving is problematic, because the behavioural and psychological processes which accompany falling asleep at the wheel may not typify the characteristics of sleep onset commonly reported under test conditions and simulations by sleep laboratories.
Driving will tend to make a driver put considerable effort into remaining awake, and in doing so, the driver will exhibit different durations and sequences of psychological and behavioural events that precede sleep onset.
As underlying sleepiness may be masked by this prefacing compensatory effort, the criteria for determining whether a subject is falling asleep may be unclear.
Indeed, the Applicants have determined by practical investigation that parameters usually accepted to indicate falling asleep are actually not reliable as an index of sleepiness if the subject is driving.
For example, although in general eye blink rate has a tendency to rise with increasing sleepiness, this rate of change is confounded by the demand, variety and so stimulus content or level of a task undertaken (eg driving), there being a negative correlation between blink rate and task difficulty.
In an attempt to prevent sleep-related vehicle accidents, it is also known passively to monitor driver working times through chronological activity logs, such as tachographs. However, these provide no active warning indication.
More generally, it is also known to monitor a whole range of machine and human factors for vehicle engineering development purposes, some merely for historic data accumulation, and other unsatisfactory attempts at `real-time` active warning.
The Applicants are not aware of any practical implementation hitherto of sleepiness detection, using relevant and proven biological factors addressing inherent body condition and capacity.
Studies and trials carried out by the Applicants have shown that there are clear discernible peaks of sleep-related vehicle accidents in the UK around 02.00-06.00 hours and 14.00-16.00 hours.
Similar time-of-day data for such accidents have been reported for the USA, Israel and Finland.
These sleep-related vehicle accident peaks are distinct from the peak times for all road traffic accidents in the UK--which are around the main commuting times of 08.00 hours and 17.00 hours.
The term `sleepiness` is used herein to embrace essentially pre-sleep conditions, rather than sleep detection itself, since, once allowed to fall asleep, it may be too late to provide useful accident avoidance warning indication or correction.
Generally, a condition or state of sleepiness dictates
a lessened awareness of surroundings and events PA1 a reduced capacity to react appropriately; and PA1 an extended reaction time. PA1 common, if not universal, underlying patterns or sleepiness (pre-conditioning); PA1 exacerbating personal factors for a particular user--driver, such as recent sleep patterns especially, recent sleep deprivation and/or disruption; PA1 with a weighting according to other factors, such as the current time of day. PA1 such inputs being individually weighted, according to contributory importance, and combined in a computational decision algorithm or model, to provide a warning indication of sleepiness.
It is known from sleep research studies that the normal human body biological or physiological activity varies with the time of day, over a 24 hour, (night-day-night) cycle--in a characteristic regular pattern, identified as the circadian rhythm, biorhythm or body clock.
The human body thus has a certain predisposition to drowsiness or sleep at certain periods during the day--especially in early morning hours and mid afternoon.
This is exacerbated by metabolic factors, in particular consumption of alcohol, rather than necessarily food per se.